Microphone arrays may be utilized to enhance processing of acoustic information, for example, to enhance speech quality during a teleconference, e.g., by filtering out background noise.
Existing microphone array implementations are configured to process information of a static array of microphone elements. For example, the microphone array may be calibrated with respect to a specific configuration of the microphone elements.
For example, “Multichannel Eigenspace Beamforming in a Reverberant Noisy Environment with Multiple Interfering Speech Signals”, S. Markovich, S. Gannot and I. Cohen, IEEE Transactions on Audio, Speech and Language Processing, Volume 17, Issue 6, pp. 1071-1086, August 2009 describes a Linearly Constrained Minimum Variance (LCMV) beamformer configured to extract desired speech signals from multi-microphone measurements. In “Subspace Tracking of Multiple Sources and its Application to Speakers Extraction”, S. Markovich-Golan, S. Gannot, and I. Cohen, The IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Dallas, Tex., USA, March, 2010, the LCMV beamformer was extended to extract desired speech signals uttered by moving speakers contaminated by competing speakers and stationary noise in a reverberant environment. The article “Blind Sampling Rate Offset Estimation and Compensation in Wireless Acoustic Sensor Networks with Application to Beamforming”, S. Markovich-Golan, S. Gannot and I. Cohen, International Workshop on Acoustic Signal Enhancement (IWAENC), Aachen, Germany, September 2012, uses a blind procedure for estimating sampling rate offsets between acoustic sensor nodes, and shows that a clock drift as low as 300 ppm may deteriorate beamformer performance significantly, thereby rendering distributed structures useless.